ZipRecruiter

Log In

1

Immunology Data Analyst Jobs (NOW HIRING)

previous pagenext page

Showing results 21-40

All JobsHealthcare JobsDoctors JobsImmunologist JobsImmunology Data Analyst Jobs

Immunology Data Analyst information

See salary details

$34K

$82.6K

$136K

How much do immunology data analyst jobs pay per year?

As of Sep 12, 2026, the average yearly pay for immunology data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What is an immunology data analyst?

An Immunology Data Analyst is a professional who analyzes and interprets complex biological data related to the immune system. They work with large datasets generated from experiments, clinical trials, or public health studies to identify patterns, trends, and meaningful insights. Their responsibilities often include data cleaning, statistical analysis, visualization, and collaborating with immunologists to support research or clinical decision-making. Proficiency in bioinformatics tools, statistical software, and a solid understanding of immunology are essential for this role. Immunology Data Analysts play a crucial role in advancing research on diseases, vaccines, and immune responses.

What are the key skills and qualifications needed to thrive as an immunology data analyst, and why are they important?

To thrive as an Immunology Data Analyst, you need a strong background in biological sciences, statistics, and data analysis, typically with a degree in biology, bioinformatics, or a related field. Familiarity with statistical software (such as R or Python), data visualization tools, and laboratory information management systems is commonly required. Attention to detail, strong problem-solving skills, and the ability to communicate complex findings clearly are valuable soft skills in this role. These competencies are crucial for accurately interpreting immunological data, supporting research objectives, and enabling effective collaboration with multidisciplinary teams.

How does an immunology data analyst typically collaborate with laboratory scientists and research teams?

Immunology Data Analysts work closely with laboratory scientists to interpret complex experimental data, ensuring that their analyses align with the goals of ongoing research projects. They often participate in team meetings to discuss findings, clarify data requirements, and troubleshoot issues related to data collection or quality. Frequent collaboration is also necessary when developing and refining bioinformatics pipelines or statistical models, as analysts rely on scientists’ expertise to contextualize data. This teamwork ensures robust, reproducible results that support scientific publications and advancements in immunological research.

What is the difference between Immunology Data Analyst vs Immunology Research Associate?

AspectImmunology Data AnalystImmunology Research Associate
Required CredentialsBachelor's degree in biology, immunology, or related field; proficiency in data analysis toolsBachelor's or master's degree in biology, immunology, or related field; laboratory skills
Work EnvironmentData analysis in office or remote settings, often collaborating with research teamsLaboratory setting conducting experiments and sample processing
Employer & Industry UsagePharmaceutical companies, biotech firms, research institutionsAcademic labs, research institutions, biotech companies

While both roles involve immunology, the Immunology Data Analyst focuses on analyzing data related to immune responses, whereas the Immunology Research Associate conducts laboratory experiments. The analyst primarily works with data sets and software, while the research associate handles lab work. Both roles are essential in advancing immunology research but differ in daily tasks and work environment.

What are popular job titles related to Immunology Data Analyst jobs?

For Immunology Data Analyst jobs, the most frequently searched job titles are:

Infographic showing various Immunology Data Analyst job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

BIOINFORMATICS PROGR 3

San Francisco, CA • On-site

University of California San Francisco
Colleges, Universities, and Professional Schools • 10K+ employees
Learn more about University of California San Franciscoexternal

Full-time

Posted 18 days ago

University Of California San Francisco rating

7.8

Company rating: 7.8 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

Job description

Job Function Summary:

Involves developing and utilizing computational tools and systems to analyze and interpret biological or other research data. Utilizes and develops algorithms, computational techniques, and statistical methodologies. Helps in the design of new experiments. Implements end-user needs in database searching and integration. Assists with maintaining the computational infrastructure, local databases, and tracks the flow of samples and information for large-scale studies. Develops analysis tools for use by lab personnel and for public dissemination.  

Custom Scope:

Uses skills as a seasoned, experienced bioinformatics programming professional with a broad understanding of computational algorithms and systems; identifies and resolves a wide range of issues / software bugs. Demonstrates good judgment in selecting methods and techniques for obtaining solutions. Operates independently. Demonstrates proficiency with modern AI coding frameworks, for example, Claude, Codex, Cursor, etc., as well as traditional SQL and Python coding.  Demonstrates proficiency with modern machine learning toolkits and approaches for classification tasks using large scale datasets, including transcriptomics, and proteomics, demonstrated proficiency using, evaluating, and optimizing protein modeling and folding approaches, including Rosetta, AlphaFold3, and others. Demonstrated track record of scholarly excellence. 

Required:

  • Bachelor's degree in biological science, computational / programming, or related area and / or equivalent experience / training.
  • Minimum 3 years of related experience
  • Thorough knowledge of bioinformatics methods, nextgen sequencing processing, applications programming, web development and data structures.
  • Thorough knowledge of Python bioinformatics programming design, modification and implementation.
  • Thoroughly proficient with design, implementation, and management of SQL relational databases, web interfaces, and linux based operating systems. 
  • Thoroughly proficient with modern LLM application development tools. 
  • Thorough knowledge of protein folding algorithms, including AlphaFold3and  deploying packages on different hardware platforms, such as local systems and/or HPCs 
  • Thorough knowledge of machine learning techniques for building predictive classifiers, including logistic regression methods, random forest, neural networks, on multi-modal data, including mass spectrometry spectra, single cell sequencing, B cell repertoire sequencing, phage immunoprecipitation, yeast display, and similar. 
  • Proficient knowledge of basic cell biology, genomics, and basic immunology. 
  • Self-motivated, work independently or as part of a team, able to learn quickly, meet deadlines, and demonstrate problem-solving skills.
  • Thorough knowledge of genomic alignment algorithms, including Diamond, Minimap2, STAR.
  • Conceptual familiarity with PhIPseq, yeast display, and antigen screening methods. 
     

Preferred:

  • Ability to interface with management on a regular basis.

  • Doctoral degree in biological science, computational / programming, or related area and / or equivalent experience / training. Ideally in machine learning applied to biomedicine areas.

Problem Solving:

  Given a large biologic dataset derived from cases and controls, construct and train a machine learning classifier, test performance on held out data, and derive key features driving classification performance

  Construct new query interfaces using APIs to commercial AI systems for analysis of large scale datasets, including agentic systems for automated data analysis and hypothesis generation

 Create a new client/server database for antigen display data, with data analysis and visualization tools.

Analyze B or T Cell receptor repertoire sequencing data for clonal expansion

Model antigen / antibody interactions using AlphaFold3

Less frequent and more complex problems solved by the employee:

 Troubleshooting SQL database issues, designing new web server frameworks.

Build new databases as needed.

Building bespoke visualization tools for new datasets  

Problems/situations that are referred to this employee's supervisor:

  Scientific strategic direction questions

  Collaboration strategy and agreements

  Acquisition of new patient cohorts for data production

% 

of time

Essential Function (Yes/No)

  

Key Responsibilities

(To be completed by Supervisor)

25

YESApplies complex bioinformatics concepts to implementexisting software tools and systems, both command line and web based for large scale analysis of in-house generated genomic, proteomic, and immunology data. . 

20

YESDevelops new analysis tools, focusing on  automated analysis, data aggregation, hypothesis generation. May include agentic systems.

15

YESDevelops, implements, and maintains web interfaces and SQL databases to share and display bioinformatics analysis and content with collaborators and other users.

10

YESPerforms complex data modeling, performance and integration testing, and builds user interfaces for a variety of internal and external constituents.

20

YESPerforms complex data analysis, including developing predictive machine learning classifiers, for in-house generated data. 

10

YESAssists with manuscript preparation, figure making, public data deposition

100%

 (To update total %, enter the amount of time in whole numbers (without the % symbol - e.g., 15, 20) then highlight the total sum (e.g., 1%) at the bottom of the column and press F9. The total sum should add up to 100%.)

What University Of California San Francisco employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply